Humanoid Robots’ ChatGPT Moment: Is Web3 the Missing link?

Have you seen or interacted with a robot today? 

If not, you likely will soon. Humanoid robots are leaving factories and entering our homes and offices. Tesla’s Optimus robot, for instance, is expected to reach commercial deployment this year and companies like Figure and Apptronik are all targeting commercial deployments in automotive factories.

At Tesla’s June 13th, 2024 annual shareholder meeting, Elon Musk remarked, “Things are gonna scale up very rapidly from here.” He envisions a world with billions of humanoid robots, potentially outnumbering humans by 2040.

Nvidia, Amazon, and others are also heavily investing in robotics innovation. Goldman Sachs projects 4.3 million humanoid units by 2030, with an estimated wage impact of $254 billion. China, meanwhile, is fast-tracking mass production of humanoids, aiming to position robotics as a key driver of economic growth. However, scaling these systems efficiently, securely, and ethically remains a significant challenge for the following reasons:

1. Security and cyber threats:
   As robots become interconnected, they’re increasingly vulnerable to cyberattacks. Malicious actors could potentially hack into robotic systems, altering their behavior and compromising safety.
2. Scalability and coordination:
   Managing billions of autonomous robots is a monumental challenge. Traditional, centralized systems are prone to bottlenecks and inefficiencies, making it difficult to coordinate robots on a global scale.
3. Ownership and data privacy:
   Robots generate vast amounts of data as they perform tasks, raising concerns about who owns this data and how it’s used. Without robust frameworks, these systems could erode user privacy.
4. Trust and accountability:
   For robots to function autonomously, there needs to be a system of trust to ensure that tasks are executed reliably and disputes are resolved transparently.

So the question remains: How do we manage, secure, and scale these systems in the long run?

Web3: The missing link?

While AI powers the brains of robots, blockchain technology can provide the backbone for their secure and decentralized management. Here’s why it matters:

1. Blockchain transparency:
   Blockchain creates a tamper-proof record of all transactions and data exchanges. This allows robots to detect malicious activity in real-time, neutralizing compromised systems.
2. Smart contracts:
   These self-executing agreements ensure robots operate as intended, preventing unauthorized access and vulnerabilities. For instance, a robot delivering groceries could autonomously negotiate payments and confirm delivery on-chain, eliminating intermediaries.
3. Decentralized coordination:
   Robots can collaborate without centralized oversight, sharing insights and tasks securely through blockchain networks.
4. Data ownership and monetization:
   Web3 introduces frameworks for tokenizing and securely sharing data. Users can own and monetize the data generated by their robots, ensuring privacy while creating new revenue streams.

Together, these technologies could open up entirely new business models. Let’s have a look at some of the pioneers in this growing sector.

How Web3 & robotics are reshaping the world already!

Robonomics Network

Robonomics Network is an example of Web3 x robotics in action, integrating robots into the human economy through smart contracts. Operating on Ethereum and Polkadot, the platform allows robots to act as autonomous economic agents. Equipped with Web3 wallets, robots can receive payments for completed tasks or pay other agents, bypassing traditional financial systems. This approach not only democratizes robotic ownership but also addresses data privacy concerns by creating transparent, decentralized systems.

Ocean Protocol

Ocean Protocol builds on this by enabling robots and IoT devices to function as autonomous economic agents through blockchain-based data tokens. In partnership with Robonomics Network, the two developed a framework allowing robots to autonomously trade data using the Robot Operating System (ROS), enabling the collection and tokenization of environmental sensor data and secure sharing of operational telemetry. The platform has shown real-world success with robots like Boston Dynamics’ Spot, which can now monetize its telemetry data for developers while maintaining secure data sharing and ensuring fair compensation for operators. 

Additionally, Ocean Protocol has created a marketplace for robotics training datasets, allowing manufacturers to monetize their data while giving developers access to high-quality, privacy-protected resources. This ecosystem fosters collaboration while maintaining decentralized ownership.

SingularityNET and Fetch.ai

While Robonomics and Ocean Protocol focus on decentralized economic integration and data sharing, SingularityNET and Fetch.ai target specific challenges in AI and process optimization.

SingularityNET’s decentralized marketplace allows developers to monetize AI algorithms, lowering costs and driving innovation. Its role in powering Sophia, the humanoid robot created by Hanson Robotics, showcases how decentralization can improve accessibility to advanced AI technologies.

Fetch.ai extends these capabilities by introducing “digital twin” agents — autonomous systems that optimize processes like supply chain logistics and energy distribution. These agents operate within decentralized ecosystems, illustrating Web3’s ability to enhance scalability, collaboration, and efficiency across industries.

Turning concept into action: practical opportunities in robotics & Web3

While the potential of robotics x Web3 is inspiring, translating these ideas into real-world projects is where true innovation happens. By launching small-scale pilots, fostering strategic collaborations, and leveraging established blockchain frameworks, entrepreneurs can build sustainable solutions that resonate with users, investors, and regulators alike. Below are practical opportunities and recommendations to guide this journey.

Here’s how entrepreneurs can start bridging the gap between vision and reality.

Examples of projects to build:

1. Decentralized robot marketplace: Create a platform where robot capabilities can be tokenized and traded. Imagine a decentralized “Fiverr for robots,” where businesses can hire robots for tasks like cleaning, security, or manufacturing, with payments handled via smart contracts.
2. Collaborative algorithm training: Build a platform where developers contribute AI models to enhance robotic behavior, incentivized by tokens. This could foster a collaborative ecosystem to improve robot intelligence while ensuring contributors are rewarded fairly.
3. Web3-enabled delivery robots: Integrate autonomous delivery robots with blockchain-based payment systems, enabling microtransactions for last-mile logistics. For instance, users could pay a robot in real time as it delivers groceries or packages as robots are already being paid via their personal wallets.

Strategic recommendation for entrepreneurs: 

To make these ideas actionable, entrepreneurs should focus on the following

1. Start small with niche applications:
   Focus on areas where robots are already gaining traction and can be easily tokenized, such as service robots in hospitality, cleaning, or healthcare. Developing small-scale, targeted solutions in these niches minimizes complexity while showcasing the value of combining robotics with Web3.
   For instance, NFTs can represent ownership or operational rights of specific robots or their learned behaviors, enabling fractional ownership. This approach allows users to own shares of a robot or its capabilities, democratizing access to advanced robotics technology and unlocking new opportunities for collaboration and innovation.
2. Leverage existing protocols:
   Reduce development barriers by building on frameworks like Robonomics Network, which supports blockchain-powered robotic systems, or Ocean Protocol, which facilitates secure data sharing. These platforms offer tools and resources to fast-track your project.
3. Micro-licensing of robotic skills
   Much like app stores sell discrete software modules, create a platform where specific robotic “skills” (e.g., image recognition, grasping algorithms) are licensed via micro-payments or NFTs. This modular approach lets entrepreneurs focus on perfecting one specialized skill — like a best-in-class drone navigation algorithm — without building an entire robot from scratch.
4. Zero-knowledge robotics
   Integrate zero-knowledge proofs (ZKPs) so robots can verify tasks or identities without revealing sensitive data. For instance, a healthcare robot might confirm it’s “qualified” to administer medication on-chain without disclosing the underlying training or confidential patient details. This approach fosters user trust and streamlines compliance with privacy laws.
5. Consider unconventional collaborations
   Partner with agri-tech startups to automate and tokenize tasks like planting, fertilizing, or irrigation. Fractional ownership tokens could fund equipment upgrades, while farmers’ data is sold on decentralized markets.

Risks and challenges:

Where there are opportunities, there exists risk. And integration of Web3, AI and robotics presents emerging risk factors that entrepreneurs should carefully consider. Privacy and data protection are paramount, as Web3’s decentralized architecture offers enhanced security, but integrating AI and robotics raises concerns about data collection and usage. 

Ensuring user consent, protecting personal information on decentralized networks, and implementing robust encryption and anonymization techniques are critical. Fairness and bias must be addressed to prevent AI systems from perpetuating or amplifying existing biases, ensuring diverse representation in governance and fair token economies. 

Human oversight and control are crucial, balancing autonomy with mechanisms like kill switches and ensuring human values are embedded in AI decision-making.

• Regulatory hurdles: Research compliance requirements in target markets especially in the EU are slowing the speed of innovation as compared to the US. Web3 Entrepreneurs need to encourage partnerships with legal experts to navigate potential barriers.
• Ethical concerns: Develop transparent governance models to ensure responsible use of robots and address public concerns about privacy and security.
• Hardware limitations: Prioritize compatibility with existing robotic platforms to avoid high upfront costs and long development cycles.

But let’s not forget the human element. The integration of these technologies must be done with a keen eye on societal impact. We must ensure that the benefits of this technological revolution are equitably distributed, that jobs are not just displaced but transformed, and that human values guide the development of these systems. 

By focusing on these practical approaches, entrepreneurs can turn abstract opportunities into real-world solutions, driving the adoption of robotics x Web3 and unlocking its transformative potential.

Conclusion: 

The fusion of robotics and Web3 is no longer a distant possibility; it’s unfolding now. As robots integrate into everything from manufacturing to healthcare, decentralized technologies provide the scalability, security, and autonomy needed to manage these complex networks. 

Entrepreneurs who tackle regulatory considerations, data ethics, and design challenges upfront can accelerate adoption while minimizing risk. This convergence is not merely about technological advancement — it’s about shaping a more collaborative, equitable, and innovative future. The opportunity is vast, and the time to act is now.

Read what else we see coming for Web3 in 2025. Onchain’s 39 Web3 Predictions for 2025 investigate questions about the future of the regulatory landscape, NFTs, DePIN, AI & blockchain, and many other widely discussed topics. Read now.